Publications

^  denotes research staff or postdoc.

^^ denotes graduate students (e.g., PhD/MSc. students)

#   denotes undergraduate students (e.g., FYP or URECA students)

Journal Papers

1. Alicioglu, Gulsum, Bo Sun, and Shen S. Ho. An Injury-Severity-Prediction-Driven Accident Prevention System, Sustainability 14, no. 11: 6569, 2022.

2. Woon Huei Chai, Shen-Shyang Ho, and Hiok Chai Quek, Representation Recovery via L1 -norm Minimization with Corrupted Data, Information Sciences, Vol. 595, pp. 395-426, 2022.

3. Woon Huei Chai, Shen-Shyang Ho, and Quek Chai A Novel Quasi-Newton Technique for Composite Convex Minimization, Pattern Recognition, Vol 122, 108281, 2022.

4. Shen-Shyang Ho, Matthew Schofield^^, Ning Wang, Learning incentivization strategy for resource rebalancing in shared services with a budget constraint, Journal of Applied Numerical Optimization, Vol. 3, Issue 1, pp. 105-114, 30 April 2021.

5. Ning Wang, Jie Li, Shen-Shyang Ho, Chenxi Qiu, Distributed machine learning for energy trading in electric distribution system of the future, The Electricity Journal, Vol.  34, Issue 1, 2021,

6. Autumn Chadwick^^, Shen-Shyang Ho, Yinan Li, and Min Wang, A Discrete Model for Bike Sharing Inventory, International Journal of Difference Equations, Vol. 15, Issue 2, 2020.

7. Fatemeh Amiri, Nasser Yazdani, Azadeh Shakery, Shen-Shyang Ho, Bayesian-based Anonymization Framework against Background Knowledge Attack in Continuous Data Publishing, Transactions on Data Privacy 12:3, 197 - 225, 2019

8. John R. Graef, Shen-Shyang Ho, Lingju Kong, Min Wang, A fractional differential equation model for bike share systems, Journal of Nonlinear Functional Analysis, Vol. 2019, Article ID 23, pp. 1-14, 2019.

9. J. T. Zhou, I. W. Tsang, S-S Ho, and K-R Müller, N-ary Decomposition for Multi-class Classification, Machine Learning Journal (ACML 2018 Journal Track), vol. 108, issue 5, pp. 809-830, May 2019.

10. J.-J. Zhao^^ and S.-S. Ho, Improving Bayesian Network Local Structure Learning via Data-driven Symmetry Correction Methods, International Journal of Approximate Reasoning, vol. 107, pp. 101-121, April 2019.

11. J. Cherian^^, J. Luo, and S.-S. Ho, ParkLoc: Light-weight Graph-based Vehicular Localization in Parking Garages, Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), vol. 2, issue 3 , September, 2018. 

12. J.-J. Zhao^^ and S.-S. Ho, Structural Knowledge Transfer for Learning Sum-Product Networks, Knowledge-Based Systems, 122, 159-166, 2017.

13. S.-S. Ho, P. Dai^, and F. Rudzicz, Manifold Learning for Multivariate Variable-length Sequences with an Application to Similarity Search, IEEE Transactions on Neural Networks and Learning Systems, 27, No. 6, 1333-1344, 2016. 

14. M. Tanveer^, M. Asif Khan, S.-S. Ho, Robust energy-based least squares twin support vector machines, Applied Intelligence, 45, No. 1, pp. 174-186, 2016.

15. M. Tanveer^, K. Shubham, M. Aldhaifallah and S.-S. Ho, An efficient regularized knn-based weighted twin support vector regression, Knowledge-Based Systems, 94. 70-87, 2016

16. Q. Wu^, J. Chen, S.-S. Ho, X. Li^, H. Min, C. Han, Multi-label Regularized Generative Model for Semi-Supervised Collective Classification in Large-Scale Networks, Big Data Research, 2, No. 4, 187-201, 2015.

17. Q. Wu^, Y. Ye, H. Zhang, T. Chow and S-S. Ho, ML-TREE: A Tree-Structure Based Approach to Multi-Label Learning, IEEE Transactions on Neural Networks and Learning Systems, 26, No. 3, 430-443, 2015.

18. P. Dai^, S. S. Ho, and F. Rudzicz, Sequential behavior prediction based on hybrid similarity and cross-user activity transfer, Knowledge-Based Systems, 77, 29-39, 2015.

19. Q. Wu^, Y. Ye, S-S. Ho, and S. Zhou, Semi-supervised multi-label collective classification ensemble for functional genomics, BMC Genomics 15, Suppl. 9, S17, 2014. 

20. Q. Wu^, Y. Ye, H. Zhang, M. K. Ng, and S-S. Ho, FORESTEXTER: An Efficient Random Forester Algorithm for Imbalanced Text Categorization, Knowledge-Based Systems, 67, 105-116, 2014. 

21. Q. Wu^, Y. Ye, M. K. Ng, S-S. Ho and R. Shi, Collective prediction of protein functions from protein-protein interaction networks, BMC Bioinformatics 15, Suppl. 2, S9, 2014.

22. S-S. Ho and S. Ruan, Preserving Privacy for Interesting Location Pattern Mining from Trajectory Data, Transactions on Data Privacy, vol. 6, no. 1, 87-106, 2013.

23. H. Wechsler and S-S. Ho, Intelligent Evidence-Based Management for Data Collection and Decision-Making Using Algorithmic Randomness and Active Learning, in Intelligent Information Management, vol. 3, no 4, 2011. [pdf]

24. S-S. Ho and H. Wechsler, A Martingale Framework for Detecting Changes in Data Streams by Testing Exchangeability, in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 32, no, 12, 2010. [pdf]

25. S.-S. Ho and H. Wechsler, Query by Transduction, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol .30, no. 9, 2008, pp 1557-1571. [pdf]

26. R. Polyak, S.-S. Ho and I. Griva, Support Vector Machine via Nonlinear Rescaling Method, in Optimization Letters, vol. 1, no. 4, 2007, 367-378.  [pdf]

27. V.C. Chen, F. Li, S.-S. Ho and H. Wechsler, Micro-Doppler effect in radar - Phenomenon , Model, and Simulation Study, IEEE Transactions on Aerospace and Electronic Systems, vol. 42, no. 1, 2006, pp 2-21. [pdf]

28. V.C. Chen, F. Li, S.-S. Ho and H. Wechsler, Analysis of micro-Doppler signatures, IEE Proc.-Radar Sonar Navig., Vol. 150, No. 4, 2003, pp 271-276. [pdf]  

Conference Papers  

1. Shen-Shyang Ho and Tarun Teja Kairamkonda^^, Change Point Detection in Evolving Graph using Martingale, 39th ACM/SIGAPP Symposium On Applied Computing, Avila, Spain, April 8 - April 12, 2024

2. Steven Arroyo^^ and Shen-Shyang Ho, Autoencoder Ensemble Method for Botnets Detection on IOT Devices, 21st IEEE International Conference on Machine Learning and Applications (ICMLA), Nassau, The Bahamas, December 12-15, 2022. 

3. Lubos Krcál, Shen-Shyang Ho, Jan Holub, Hierarchical Bitmap Indexing for Range Queries on Multidimensional Arrays, 27th International Conference on Database Systems for Advanced Applications (DASFAA-2022), April 11-14, 2022, Hyderabad, India.

4. Dylan Perry#, Ning Wang, Shen-Shyang Ho, Energy Demand Prediction with Optimized Clustering-Based Federated Learning, IEEE Global Communications Conference (GLOBECOM), Madrid, Spain, Dec. 7-11, 2021.

5. Hieu Nguyen, Lucas Lavalva#, Shen-Shyang Ho, Mohammed Khan^^ and Nicholas Kaegi#, Optimal N-ary ECOC Matrices for Ensemble Classification, 2021 IEEE Symposium Series on Computational Intelligence (SSCI) (SSCI 2021), Orlando, FL, Dec. 4-7, 2021. 

6. Hieu D. Nguyen, Mohammed Sarosh Khan^^, Nicholas Kaegi#, Shen-Shyang Ho, Jonathan Moore#, Logan Borys#, Lucas Lavalva#, Ensemble Learning using Error Correcting Output Codes: New Classification Error Bounds, 33rd IEEE International Conference on Tools with Artificial Intelligence (ICTAI2021), November 1-3, 2021.

7. Matthew Schofield^^, Shen-Shyang Ho, and Ning Wang, Handling Rebalancing Problem in Shared Mobility Services via Reinforcement Learning-based Incentive Mechanism, 24th IEEE International Conference on Intelligent Transportation (ITSC),  Indianapolis, IN, Sep 19-22, 2021.

8.  Paolo Rommel Sanchez^^, Hong Zhang, Shen-Shyang Ho, and Eldon de Padua, Comparison of One-Stage Object Detection Models for Weed Detection in Mulched Onions, IEEE International Conference on Imaging Systems and Techniques, New York, NY, Aug 24-26, 2021.

9. Shen-Shyang Ho, Matthew Marchiano#, Hieu Duc Nguyen, and Scott Zockoll#, An Error-Correcting Output Code Framework for Lifelong Learning without a Teacher, 32nd IEEE International Conference on Tools with Artificial Intelligence (ICTAI), 2020

10. Gulsum Alicioglu^^, Bo Sun and Shen Shyang Ho, Assessing Accident Risk using Ordinal Regression and Multinomial Logistic Regression Data Generation, IEEE International Joint Conference on Neural Networks (IJCNN), 2020.

11. Shen-Shyang Ho, Matthew Schofield#, Bo Sun, Jason Snouffer, Jean Kirschner, A Martingale-based Approach for Flight Behavior Anomaly Detection, 20th IEEE International Conference on Mobile Data Management (MDM 2019), Hong Kong, China, June 10-13, 2019.

12. W.-H. Chai^^, S.-S. Ho, C.-K. Goh, and H. C. Quek, A Fast Sparse Reconstruction Approach for High Dimensional Image-based Object Surface Anomaly Detection, 15th IAPR Conference on Machine Vision Applications (MVA), Nagoya, Japan, May 8-12, 2017.

13. P.-H. Chen^ and S.-S. Ho, Is OVERFEAT Useful for Image-based Surface Defect Classification Task?, 23rd IEEE International Conference on Image Processing (ICIP), Phoenix, Arizona, USA, September 25-28, 2016

14. J. Cherian^^, J. Luo, S.-S. Ho, H. Guo^ and R. Wisbrun, ParkGauge: Gauging the Occupancy of Parking Garages with Crowdsensed Parking Characteristics, 17th IEEE International Conference on Mobile Data Management (MDM), Porto, Portugal, 13-16 June, 2016

15. W. H. Chai^^, S.-S. Ho, C.-K. Goh, Exploiting Sparsity for Image-based Object Surface Anomaly Detection, 41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Shanghai, China, March 20-25, 2016

16. J. T. Zhou^^, S. J. Pan, I. W. Tsang, and S-S. Ho, Transfer Learning for Cross-Language Text Categorization through Active Correspondences Construction, 13th AAAI Conference on Artificial Intelligence (AAAI), Phoenix, AZ, 12-17 February, 2016.

17. P. Dai^ and S-S. Ho, A Smartphone User Activity Prediction Framework Utilizing Partial Repetitive and Landmark Behaviors, 15th IEEE International Conference on Mobile Data Management (MDM), Brisbane, Australia, 14-18 July, 2014. 

18. W. H. Chai^^, H. Guo^, and S.-S. Ho, Robust Prediction in Nearly Periodic Time Series using Motifs, International Joint Conference on Neural Networks (IJCNN), Beijing, China, July 6-11, 2014. 

19. R. Shi, Q. Wu^, Y. Ye, and S.-S. Ho, A Generative Model with Network Regularization for Semi-Supervised Collective Classification, SIAM International Conference on Data Mining (SDM), Philadelphia, PA, Apr. 24-26, 2014. 

20. Q. Wu^, Y. Ye, X. Zhang, and S.-S. Ho, Cluster Tree based Multi-Label Classification for Protein Function Prediction, IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Shanghai, China, Dec. 18-21, 2013. 

21. P. Dai^, W. Yang#, and S.-S. Ho, Predicting Mobile Call Behavior via Subspace Methods, International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction (SBP), Washington, DC, Apr. 2-5, 2013.

22. S.-S. Ho, Mining Multivariate Spatiotemporal Patterns from Heterogeneous Mobility Data, Proc. 20th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Redondo Beach, California, Nov. 6-9, 2012.

23. S.-S. Ho, An Effective Vortex Detection Approach for Velocity Vector Field, Proc. 21st International Conference on Pattern Recognition (ICPR), Tsukuba, Japan, Nov 11-15, 2012. 

24. S.-S. Ho, Preserving Privacy for Moving Objects Data Mining, Proc. International Conference on Intelligence and Security Informatics (ISI), Washington, DC, July 14-17, 2012. 

25. S.-S. Ho, W. Tang, and W. T. Liu, Tropical Cyclone Event Sequence Similarity Search via Dimensionality Reduction and Metric Learning, Proc. 16th ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining, Washington, DC, July 25-28, 2010. [video][pdf]

26. S.-S. Ho, W. Tang, W. T. Liu, and M. Schneider, A Framework for Moving Sensor Data Query and Retrieval for Dynamic Atmospheric Events, Proc. 22nd International Conference on Scientific and Statistical Database Management (SSDBM), Heidelberg, Germany, Jun 30-July 2, 2010. [pdf]

27. A. Panangadan, S.-S. Ho, and A. Talukder, Cyclone Tracking using Multiple Satellite Image Sources, Proc. of 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Seattle, WA, 4-6 Nov, 2009. [pdf]

28. S.-S. Ho and A. Talukder, Automated Cyclone Discovery and Tracking using Multiple Heterogeneous Satellite Data, Proc. 14th ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining, Las Vegas, NV, 24-27 Aug, 2008. [pdf]

29. S.-S. Ho and R. Polyak, Confident Identification of Relevant Objects Based on Nonlinear Rescaling Method and Transductive Inference,  Proc. 7th Int. Conf. on Data Mining (ICDM 2007), Omaha, NE, Oct. 28 - 31, 2007. [pdf]

30. S.-S. Ho and H. Wechsler, Detecting Change-Points in Unlabeled Data Streams using Martingale, Proc. 20th Int. Joint. Conf. Artificial Intelligence (IJCAI 2007), Hyderabad, India, Jan. 6 - 12, 2007. [pdf]

31. S.-S. Ho, A Martingale Framework for Concept Change Detection in Time-Varying Data Streams, Proc Int. Conf. on Machine Learning (ICML 2005), Bonn, Germany, Aug. 7 - 11, 2005 [pdf]

32. S.-S. Ho and H. Wechsler, Adaptive Support Vector Machine for Time-Varying Data streams Using the Martingale, Proc. Int. Joint Conf. on Artificial Intelligence (IJCAI 2005), Edinburgh, Scotland, July 30 - Aug. 5, 2005 [pdf]

33. S.-S. Ho and H. Wechsler, On the detection of concept change in time-varying data streams by testing exchangeability, Proc. Conference on Uncertainty in Artificial Intelligence (UAI 2005), Edinburgh, Scotland, July 26 - 29, 2005 [pdf]

34. S.-S. Ho and H. Wechsler, Transductive Confidence Machines for Active Learning, Proc. Int. Joint Conf. Neural Network (IJCNN 2003), Seattle, July 2003 [pdf]

Workshop Papers  

1. Nicholas Bovee, Stephen Piccolo#, Shen Shyang Ho, and Ning Wang Experimental test-bed for Computation Offloading for Cooperative Inference on Edge Devices, EdgeComm: The Fourth Work-shop on Edge Computing and Communications (at ACM/IEEE Symposium on Edge Computing), December 9, 2023, Wilmington, DE

2. Purva Makarand Mhasakar, Kevin Doshi, Ning Wang, Shen Shyang Ho, and Haibin Ling, Distributed Tracking and Verifying: A Real-Time and High-Accuracy Visual Tracking Edge Computing Framework for Internet of Things, EdgeComm: The Fourth Workshop on Edge Computing and Communications (at ACM/IEEE Symposium on Edge Computing), December 9, 2023, Wilmington, DE

3. Lahari Soumya Voleti^^ and Shen-Shyang Ho, Personalized Learning with Limited Data on Edge Devices using Federated Learning and Meta-Learning, EdgeComm: The Fourth Workshop on Edge Computing and Communications (at ACM/IEEE Symposium on Edge Computing), December 9, 2023, Wilmington, DE

4. Alex Lam#, Matthew Schofield#, and Shen-Shyang Ho. 2019. Detecting (Unusual) Events in Urban Areas using Bike-Sharing Data. In 3rd ACM SIGSPATIAL InternationalWorkshop on Analytics for Local Events and News (LENS’19), November 5, 2019, Chicago, IL, USA. ACM, New York, NY, USA, 7 pages.

5. Sun, Bo Beth, Eric Zielonka#, Aleksandr Fritz^^, Matthew Schofield#, Brennan Ringel#, Brendan Armstrong#, Shen-Shyang Ho, Anthony Breitzman, et al. "Visual Analytics for Real-Time Flight Behavior Threat Assessment." 2018 IEEE International Conference on Big Data (Big Data) Workshop, pp. 3607-3612., IEEE, 2018.

6. L. Krčál^ and S-S. Ho, SciDB-based Framework for Efficient Satellite Data Storage and Query based on Dynamic Atmospheric Event Trajectory", ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data (BigSpatial), Seattle, WA, 3 Nov. 2015

7. S.-S. Ho, M. Lieberman, P. Wang, and H. Samet, Mining Future Spatiotemporal Events and their Sentiment from Online News Articles for Location-Aware Recommendation System, ACM SIGSPATIAL MobiGIS, Redondo Beach, CA, 6 Nov. 2012. 

8. S.-S. Ho and S. Ruan, Differential Privacy for Location Pattern Mining, Fourth ACM SIGSPATIAL International Workshop on Security and Privacy in GIS and LBS (SPRINGL), Chicago, IL, 1 Nov, 2011. [pdf]

9. S.-S. Ho, Utilizing Spatio-Temporal Text Information for Cyclone Eye Annotation in Satellite Data, IJCAI workshop on Cross-Media Information Access and Mining, Pasadena, CA, 13 July, 2009. [pdf]

10. A. Talukder and S.-S. Ho, Classification from Disparate Multiple Streaming Data Sources, NIPS-08 workshop, Learning from Multiple Sources, Vancouver, Canada, 13 Dec, 2008. [pdf]

11. S.-S. Ho and A. Talukder, Cyclone Tracking Using Multiple Satellite Data Sources via Spatial-Temporal Knowledge Transfer, AAAI-08 workshop, Transfer Learning for Complex Tasks, Chicago, IL, 14 July, 2008. [pdf]

12. S-S Ho and H. Wechsler, Learning from data streams via online transduction , ICDM 2004 Workshop on Temporal Data Mining: Algorithms, Theory and Applications (TDM 2004), Brighton, UK, Nov 2004. [pdf]

Conference Demo and Poster

1. Steven Arroyo^^ and Shen-Shyang Ho, A Hybrid-Cloud Autoencoder Ensemble Method for BotNets Detection on Edge Devices, 8th IEEE International Conference on Fog and Edge Computing (ICFEC 2024), Philadelphia, PA, May 6-9, 2024

2. Shen-Shyang Ho, Paolo Rommel Sanchez, Nicholas Bovee, Suraj Bitla^^, Gopi Krishna Patapanchala^^  and Stephen Piccolo#, Computation Offloading for Precision Agriculture using Cooperative Inference, 8th IEEE International Conference on Fog and Edge Computing (ICFEC 2024), Philadelphia, PA, May 6-9, 2024

3. Nicholas Bovee, Stephen Piccolo#, Suraj Bitla^^, Gopi Krishna Patapanchala^^ and Shen-Shyang Ho, SplitTracer: A Cooperative Inference Evaluation Toolkit for Computation Offloading on the Edge, 8th IEEE International Conference on Fog and Edge Computing (ICFEC 2024), Philadelphia, PA, May 6-9, 2024

4. Matthew Schofield^^, Ning Wang, and S-S. Ho, Rebalancing Shared Mobility Systems by User Incentive Schemes: State-Action Representation Design and Analysis, 39th ACM/SIGAPP Symposium On Applied Computing, Avila, Spain, April 8 - April 12, 2024

5. H. Guo^, Y. Dong#, and S-S. Ho, Stochastic Location Optimization in a Dynamic Environment, Proc. 23th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Seattle, WA, Nov. 3-6, 2015.

6. J. Cherian^^, J. Luo, H. Guo^, S-S. Ho, and R. Wisbrun, ParkGauge: Gauging the Congestion Level of Parking Garages with Crowdsensed Parking Characteristics, Proc. 13th ACM Conference on Embedded Networked Sensor Systems (SenSys), Seoul, South Korea, Nov. 1-4, 2015. 

7. W. H. Yan#, J. Ong#, S-S. Ho and J. Cherian^^, Traffic Incident Validation and Correlation Using Text Alerts and Images, Proc. 22th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Dallas, TX, Nov. 6-8, 2014. 

Non-CS Conference/Workshop Papers/Posters 

1. John Kiger,  Shen-Shyang Ho, Vahid Heydari, Malware Binary Image Classification Using Convolutional Neural Networks, 17th International Conference on Cyber Warfare and Security, Vol. 17, No. 1, 2022

2. P. Dibona^^ and S-S. Ho, Automated information foraging for sensemaking, SPIE Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications, April 2019.

3. L. Krčál^ and S-S. Ho, Supporting Research using Satellite Data: A Framework for Spatiotemporal Queries in SciDB, AGU Fall Meeting, Dec. 14-18, San Francisco, CA, 2015.

4. L. Krčál^ and S-S. Ho, Spatiotemporal Features Representation and Queries of Large-Scale Satellite Data in SciDB, Asia Oceania Geosciences Society (AOGS) 12th Annual Meeting, August 2-7, Singapore, 2015.

5. S-S. Ho, W. Tang, and K.-S. Kuo, Ad-hoc Event-based Satellite Data Query and Retrieval for Climate Informatics, First International Climate Informatics Workshop, August 26, New York, NY, 2011.

6. M. Schneider, S.-S. Ho, M. Agrawal, T. Chen, H. Liu, G. Viswanathan, A Moving Objects Database Infrastructure for Hurricane Research: Data Integration and Complex Object Management, Earth Science Technology Forum, June 21-23, Pasadena, CA, 2011. 

7. M. Schneider, S.-S. Ho, T. Chen, A. Khan, G Viswanathan, W. Tang, and W. T. Liu,  Moving Objects Database Technology for Ad-Hoc Querying and Satellite Data Retrieval of Dynamic  Atmospheric Events, 2010 Earth Science Technology Forum, June 22-24, Arlington, VA, 2010. 

8. A. Talukder and S.-S. Ho, Remote Event Detection and Tracking using Multiple Heterogeneous Satellite Data Fusion'', Proc. of SPIE, Optical Pattern Recognition XX, Orlando, Florida, 16-17 April, 2009. (Invited Paper) [pdf]

9. S.-S. Ho and A. Talukder, Automated Cyclone Tracking using Multiple Remote Satellite Data via Knowledge Transfer, IEEE Aerospace Conference 2009, Big Sky, MT, 7-14 March, 2009. [pdf]

10. S.-S. Ho, A. Talukder, T. Liu, W. Tang, and A. Bingham, Automated Historical and Real-time Cyclone Discovery with Multi-model Remote Satellite Measurements, American Geophysical Union Fall Meeting, San Francisco, CA, 15-19 December, 2008 [Extended Abstract]

11. A. Talukder, S.-S. Ho, T. Liu, W. Tang, A. Bingham, and E. Rigor, Global Cyclone Detection and Tracking using Multiple Remote Satellite Data, NASA Earth Science Technology Conference, Aldephi, MD, 24 June, 2008. [pdf] 

12. S.-S. Ho and A. Talukder, Automated Cyclone Identification from Remote QuikSCAT Satellite Data, IEEE Aerospace Conference 2008, Big Sky, MT, Mar. 1-8, 2008. [pdf]

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